Concentration Fluctuations and Segmental Dynamics in Weakly Dynamic Asymmetric Blends in the Presence of Surface-Functionalized Multiwall Carbon Nanotubes

Surface-functionalized multiwall carbon nanotubes (MWCNTs) are incorporated in poly(methyl methacrylate)/styrene acrylonitrile (PMMA/SAN) blends and the pretransitional regime is monitored in situ by melt rheology and dielectric spectroscopy. As the blends exhibit weak dynamic asymmetry, the obvious transitions in the melt rheology due to thermal concentration fluctuations are weak. This is further supported by the weak temperature dependence of the correlation length ( approximate to 10-12 angstrom) in the vicinity of demixing. Hence, various rheological techniques in both the temperature and frequency domains are adopted to evaluate the demixing temperature. The spinodal decomposition temperature is manifested in an increase in the miscibility gap in the presence of MWCNTs. Furthermore, MWCNTs lead to a significant slowdown of the segmental dynamics in the blends. Thermally induced phase separation in the PMMA/SAN blends lead to selective localization of MWCNTs in the PMMA phase. This further manifests itself in a significant increase in the melt conductivity.

Formulation of a mathematical approach to regional frequency analysis

Estimation of design quantiles of hydrometeorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on index-flood approach and L-moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real-world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach (PA) in predicting quantiles for ungauged sites is demonstrated through Monte Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the PA outperforms methods based on index-flood approach.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

EESM-Based Link Adaptation in Point-to-Point and Multi-Cell OFDM Systems: Modeling and Analysis

In contemporary wideband orthogonal frequency division multiplexing (OFDM) systems, such as Long Term Evolution (LTE) and WiMAX, different subcarriers over which a codeword is transmitted may experience different signal-to-noise-ratios (SNRs). Thus, adaptive modulation and coding (AMC) in these systems is driven by a vector of subcarrier SNRs experienced by the codeword, and is more involved. Exponential effective SNR mapping (EESM) simplifies the problem by mapping this vector into a single equivalent fiat-fading SNR. Analysis of AMC using EESM is challenging owing to its non-linear nature and its dependence on the modulation and coding scheme. We first propose a novel statistical model for the EESM, which is based on the Beta distribution. It is motivated by the central limit approximation for random variables with a finite support. It is simpler and as accurate as the more involved ad hoc models proposed earlier. Using it, we develop novel expressions for the throughput of a point-to-point OFDM link with multi-antenna diversity that uses EESM for AMC. We then analyze a general, multi-cell OFDM deployment with co-channel interference for various frequency-domain schedulers. Extensive results based on LTE and WiMAX are presented to verify the model and analysis, and gain new insights.

Nearly Constant Switching Frequency Hysteresis Current Controller with Fast Online Computation of Boundary for a 2-Level Induction Motor Drive

A nearly constant switching frequency current hysteresis controller for a 2-level inverter fed induction motor drive is proposed in this paper: The salient features of this controller are fast dynamics for the current, inherent protection against overloads and less switching frequency variation. The large variation of switching frequency as in the conventional hysteresis controller is avoided by defining a current-error boundary which is obtained from the current-error trajectory of the standard space vector PWM. The current-error boundary is computed at every sampling interval based on the induction machine parameters and from the estimated fundamental stator voltage. The stator currents are always monitored and when the current-error exceeds the boundary, voltage space vector is switched to reduce the current-error. The proposed boundary computation algorithm is applicable in linear and over-modulation region and it is simple to implement in any standard digital signal processor: Detailed experimental verification is done using a 7.5 kW induction motor and the results are given to show the performance of the drive at various operating conditions and validate the proposed advantages.

Observation of localized states in atomically thin MoS2 field effect transistor

We present electrical transport arid low frequency (1/f) noise measurements on mechanically exfoliated single, In and triLayer MoS2-based FPI devices on Si/SiO2 substrate. We find that tie electronic states hi MoS2 are localized at low temperatures (T) and conduction happens through variable range hopping (VRH). A steep increase of 1/f noise with decreasing T, typical for localized regime was observed in all of our devices. From gate voltage dependence of noise, we find that the noise power is inversely proportional to square of the number density (proportional to 1/n(2)) for a wide range of T, indicating number density fluctuations to be the dominant source of 1/f noise in these MoS2 FETs.

Copula-Based Modeling of TMI Brightness Temperature With Rainfall Type

Overland rain retrieval using spaceborne microwave radiometer offers a myriad of complications as land presents itself as a radiometrically warm and highly variable background. Hence, land rainfall algorithms of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) have traditionally incorporated empirical relations of microwave brightness temperature (Tb) with rain rate, rather than relying on physically based radiative transfer modeling of rainfall (as implemented in the TMI ocean algorithm). In this paper, sensitivity analysis is conducted using the Spearman rank correlation coefficient as benchmark, to estimate the best combination of TMI low-frequency channels that are highly sensitive to the near surface rainfall rate from the TRMM Precipitation Radar (PR). Results indicate that the TMI channel combinations not only contain information about rainfall wherein liquid water drops are the dominant hydrometeors but also aid in surface noise reduction over a predominantly vegetative land surface background. Furthermore, the variations of rainfall signature in these channel combinations are not understood properly due to their inherent uncertainties and highly nonlinear relationship with rainfall. Copula theory is a powerful tool to characterize the dependence between complex hydrological variables as well as aid in uncertainty modeling by ensemble generation. Hence, this paper proposes a regional model using Archimedean copulas, to study the dependence of TMI channel combinations with respect to precipitation, over the land regions of Mahanadi basin, India, using version 7 orbital data from the passive and active sensors on board TRMM, namely, TMI and PR. Studies conducted for different rainfall regimes over the study area show the suitability of Clayton and Gumbel copulas for modeling convective and stratiform rainfall types for the majority of the intraseasonal months. Furthermore, large ensembles of TMI Tb (from the most sensitive TMI channel combination) were generated conditional on various quantiles (25th, 50th, 75th, and 95th) of the convective and the stratiform rainfall. Comparatively greater ambiguity was observed to model extreme values of the convective rain type. Finally, the efficiency of the proposed model was tested by comparing the results with traditionally employed linear and quadratic models. Results reveal the superior performance of the proposed copula-based technique.

Temperature dependent magnetic, dielectric and Raman studies of partially disordered La2NiMnO6

We report a detailed magnetic, dielectric and Raman studies on partially disordered and biphasic double perovskite La2NiMnO6. DC and AC magnetic susceptibility measurements show two magnetic anomalies at T-C1 similar to 270 K and T-C2 similar to 240 K, which may indicate the ferromagnetic ordering of the monoclinic and rhombohedral phases, respectively. A broad peak at a lower temperature (T-sg similar to 70 K) is also observed indicating a spin-glass transition due to partial anti-site disorder of Ni2+ and Mn4+ ions. Unlike the pure monoclinic phase, the biphasic compound exhibits a broad but a clear dielectric anomaly around 270 K which is a signature of magneto-dielectric effect. Temperature-dependent Raman studies between the temperature range 12-300 K in a wide spectral range from 220 cm(-1) to 1530 cm(-1) reveal a strong renormalization of the first as well as second-order Raman modes associated with the (Ni/Mn)O-6 octahedra near T-C1 implying a strong spin-phonon coupling. In addition, an anomaly is seen in the vicinity of spin-glass transition temperature in the temperature dependence of the frequency of the anti-symmetric stretching vibration of the octahedra. (C) 2014 Elsevier Ltd. All rights reserved.

Hysteresis current controller for a general n-level inverter fed drive with online current error boundary computation and nearly constant switching frequency

A space vector-based hysteresis current controller for any general n-level three phase inverter fed induction motor drive is proposed in this study. It offers fast dynamics, inherent overload protection and low harmonic distortion for the phase voltages and currents. The controller performs online current error boundary calculations and a nearly constant switching frequency is obtained throughout the linear modulation range. The proposed scheme uses only the adjacent voltage vectors of the present sector, similar to space vector pulse-width modulation and exhibits fast dynamic behaviour under different transient conditions. The steps involved in the boundary calculation include the estimation of phase voltages from the current ripple, computation of switching time and voltage error vectors. Experimental results are given to show the performance of the drive at various speeds, effect of sudden change of the load, acceleration, speed reversal and validate the proposed advantages.

A Nearly Constant Switching Frequency Current Error Space Vector Based Hysteresis Controller for an IM Drive with 12-sided Polygonal Voltage Space Vectors

In this paper, a current error space vector (CESV) based hysteresis controller for a 12-sided polygonal voltage space vector inverter fed induction motor (IM) drive is proposed, for the first time. An open-end winding configuration is used for the induction motor. The proposed controller uses parabolic boundary with generalized vector selection logic for all sectors. The drive scheme is first studied with a space vector based PWM (SVPWM) control and from this the current error space phasor boundary is obtained. This current error space phasor boundary is approximated with four parabolas and then the system is run with space phasor based hysteresis PWM controller by limiting the CESV within the parabolic boundary. The proposed controller has increased modulation range, absence of 5th and 7th order harmonics for the entire modulation range, nearly constant switching frequency, fast dynamic response with smooth transition to the over modulation region and a simple controller implementation.

Regional flood frequency analysis using kernel- based fuzzy clustering approach

Regionalization approaches are widely used in water resources engineering to identify hydrologically homogeneous groups of watersheds that are referred to as regions. Pooled information from sites (depicting watersheds) in a region forms the basis to estimate quantiles associated with hydrological extreme events at ungauged/sparsely gauged sites in the region. Conventional regionalization approaches can be effective when watersheds (data points) corresponding to different regions can be separated using straight lines or linear planes in the space of watershed related attributes. In this paper, a kernel-based Fuzzy c-means (KFCM) clustering approach is presented for use in situations where such linear separation of regions cannot be accomplished. The approach uses kernel-based functions to map the data points from the attribute space to a higher-dimensional space where they can be separated into regions by linear planes. A procedure to determine optimal number of regions with the KFCM approach is suggested. Further, formulations to estimate flood quantiles at ungauged sites with the approach are developed. Effectiveness of the approach is demonstrated through Monte-Carlo simulation experiments and a case study on watersheds in United States. Comparison of results with those based on conventional Fuzzy c-means clustering, Region-of-influence approach and a prior study indicate that KFCM approach outperforms the other approaches in forming regions that are closer to being statistically homogeneous and in estimating flood quantiles at ungauged sites. Key Points Kernel-based regionalization approach is presented for flood frequency analysis Kernel procedure to estimate flood quantiles at ungauged sites is developed A set of fuzzy regions is delineated in Ohio, USA

A VARIABLE SWITCHING FREQUENCY PWM TECHNIQUE FOR INVERTER-FED INDUCTION MOTOR TO ACHIEVE SPREAD SPECTRUM

Voltage Source Inverter (VSI) fed induction motors are widely used in variable speed applications. For inverters using fixed switching frequency PWM, the output harmonic spectra are located at a few discrete frequencies. The ac motordrives powered by these inverters cause acoustic noise. This paper proposes a new variable switching frequency pwm technique and compares its performance with constant switching frequency pwm technique. It is shown that the proposed technique leads to spread spectra of voltages and currents. Also this technique ensures that no lower order harmonics are present and the current THD is comparable to that of fixed switching frequency PWM and is even better for higher modulation indices.